code: def __init__(self, in_channels: int, grow_channels: int):
      super().__init__()
      self.conv1 = nn.Conv2d(in_channels, grow_channels, 3, 1, 1)
      self.conv2 = nn.Conv2d(
          in_channels + grow_channels, grow_channels, 3, 1, 1
      )
      self.conv3 = nn.Conv2d(
          in_channels + 2 * grow_channels, grow_channels, 3, 1, 1
      )
      self.conv4 = nn.Conv2d(
          in_channels + 3 * grow_channels, grow_channels, 3, 1, 1
      )
      self.conv5 = nn.Conv2d(
          in_channels + 4 * grow_channels, in_channels, 3, 1, 1
      )
      self.lrelu = nn.LeakyReLU(negative_slope=0.2, inplace=True)
  
file_path: carefree-learn/cflearn/models/cv/translator/rrdb.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch import Tensor
  from typing import Optional
  from ....schema import IDLModel
label_desc: Use image node_id 1 to create a new ResidualDenseBlock object from inherited base classes: nn with example: obj = ResidualDenseBlock(in_channels, grow_channels)